Digital Mammographic Computer Aided Diagnosis (CAD) using Adaptive Level Set Segmentation.

Digital Mammographic Computer Aided Diagnosis (CAD) using Adaptive Level Set Segmentation. Research Abstract Details 

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Digital Mammographic Computer Aided Diagnosis (CAD) using Adaptive Level Set Segmentation. Abstract Text:

John E Ball,Lori Mann Bruce,

We present a mammographic computer aided diagnosis (CAD) system, which uses an adaptive level set segmentation method (ALSSM), which segments suspicious masses in the polar domain and adaptively adjusts the border threshold at each angle to provide high-quality segmentation results. The primary contribution of this paper is the adaptive speed function for controlling level set segmentation. To assess the efficacy of the system, 60 relatively difficult cases (30 benign, 30 malignant) from the Digital Database of Screening Mammography (DDSM) are analyzed. The segmentation efficacy is analyzed qualitatively via visual inspection and quantitatively via the area under the receiver operating characteristics (ROC) curve (AZ) and classification accuracies. For the ALSSM, the best results are 87% overall accuracy, AZ=0.9687 with 28/30 malignant cases detected. The qualitative and quantitative results show that the ALSSM provides excellent segmentation and classification results and compares favorably to previous CAD systems in the literature which also used the DDSM database.

Digital Mammographic Computer Aided Diagnosis (CAD) using Adaptive Level Set Segmentation. Publishing Authors By Initials

JE Ball,LM Bruce,

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Digital Mammographic Computer Aided Diagnosis (CAD) using Adaptive Level Set Segmentation. Journal Published:

PUBLICATION TYPE: Journal Article

Journal: Conference proceedings : ... Annual International

VOLUME: 1

Page Numbers: 4973-8

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ISSN: 1557-170X

DAY: 16

MONTH: 11

YEAR: 2007

Digital Mammographic Computer Aided Diagnosis (CAD) using Adaptive Level Set Segmentation. Information

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LANGUAGE: eng

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AFFILIATION: Graduate Student Member, IEEE, Navy Surface Warfare Center, Dahlgren, VA 22485, USA. e-mail: john.e.ball@navy.mil.

Country: United States

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